Archive | IT and politics

This New York Timesarticle about Edward Snowden implicitly highlights the perceived dilemmas of US cybersecurity policy.

In 2010, while working for a National Security Agency contractor, Edward J. Snowden learned to be a hacker. He took a course that trains security professionals to think like hackers and understand their techniques, all with the intent of turning out “certified ethical hackers” who can better defend their employers’ networks. But the certification, listed on a résumé that Mr. Snowden later prepared, would also have given him some of the skills he needed to rummage undetected through N.S.A. computer systems and gather the highly classified surveillance documents that he leaked last month, security experts say.

Some intelligence experts say that the types of files he improperly downloaded at Booz Allen suggest that he had shifted to the offensive side of electronic spying or cyberwarfare, in which the N.S.A. examines other nations’ computer systems to steal information or to prepare attacks. The N.S.A.’s director, Gen. Keith B. Alexander, has encouraged workers to try their skills both defensively and offensively, and moving to offense from defense is a common career pattern, officials say. Continue Reading →

Social networking sites, such as Twitter, Facebook or Tumblr, appear to be playing a prominent role in the coordination of the still ongoing protests in Turkey. There is abundant evidence suggesting that social media have been pivotal in the spread of information, especially in the absence of coverage by traditional media [1]; to recruit and mobilize protesters [2]; to coordinate the movement without the infrastructure of formal organizations [3]; and to draw the attention and support of the international community [4]. That social media is at the heart of these protests was defiantly acknowledged by the Turkish Prime Minister himself when he described them as “the worst menace to society” [5]. There are also reports that 25 people were arrested because of their use of Twitter to spread information about the protest [6]. Continue Reading →

I’m a judge in a new competition sponsored by ChallengePost that seeks new “apps to educate people about partisan gridlock and help empower them to do something about it.” You can see more details at the link. There is $5000 in prize money at stake.

I’ve put the press release after the jump. I’m quoted saying:

People hate gridlock and want government to do something. But people also disagree about what exactly it’s supposed to do — which is precisely what creates gridlock. This competition offers an opportunity to address this fundamental tension and generate innovations that can educate and enlighten citizens.

This gets at things I’ve written before, and at some of my frustrations with the new tools that people are creating to encourage engagement with politics. These tools are often offered up as helping to solve challenges our political system faces—like gridlock or polarization—but rarely do their developers acknowledge that the very people likely to use such tools are the ones who have the sorts of strong opinions that create polarization and gridlock! In other words, it’s hard to empower the sorts of voices that will militate for moderation and compromise, if that’s your goal. People tend to militate for the policies they support, but of course other people support difference policies, and we often get stalemate.

Hopefully some creative people can develop apps that navigate this conundrum. So apply!

Many members of Congress are on Twitter, and we can track, via a site like Tweet Congress, how often these members tweet and how many people follow them. But what we still do not know is how members of Congress use Twitter. A recent study on the use of Twitter reports that most of what people do on Twitter is “pointless babble.” Do members of Congress also use tweet endlessly about what they had for lunch? What do they tweet about?

I led a group of researchers from Sam Houston State University that set out to figure out what members of the House and their competitors were tweeting about in the last two months of the 2012 election. In total, 67,119 tweets were coded for 1,119 individuals. On average, candidates for the U.S. House tweeted 88 times over the last two months of their campaign, and most of what they were tweeting about was in reference to their campaign. Only 29% of the tweets were “personal” (or “pointless babble”). The rest of their time was spent tweeting about their campaign, trying to mobilize their supporters, attacking their opponents, attacking the opposing party or presidential candidate, linking up stories about them in the news media, and discussing important issues in American politics. On average, candidates also communicated directly with their followers 13 times.

The results also show that no two candidates tweet alike. There were partisan, gender, and race specific differences.

Republicans were more likely to attack the Democratic Party and President Obama, but otherwise used Twitter at comparable rates and styles to their Democratic rivals. Third party candidates, however, used Twitter extensively if they had an account (most did not). One candidate (Steve Carlson, a Tea Party candidate from Minnesota’s 4th district) tweeted over 1,100 times during the last two months and tweeted about President Obama 282 times.

Women candidates were more active Twitter users (having more followers and tweeting more often). Women were significantly more likely to attack their opponents and use mobilization, campaign, and issue-based tweets.

While incumbents had more followers, challengers spent significantly more time tweeting about their campaign. Challengers were more likely to tweet attacks, talk about their campaign stops, link up media reports, and interact with other Twitter users.

Competitiveness also mattered. While those in competitive races tweeted at about the same rates as those in safe districts, they tweeted differently. Those in competitive races were significantly more likely to use attack tweets than those in safe races. They were also more likely to try to mobilize their followers. Those in safe districts, on the other hand, were more likely to attack the opposing party and presidential candidate.

For more information on the coding method or questions about the availability of data, please contact me.

The recent Mandiant report has spurred a lot of debate over whether the US and China are moving towards more confrontational relations over cybersecurity. In a recent paper, Erik Gartzke argues that any confrontations are likely to be very limited. Gartzke is pushing back against the prevalent claim that the US is unprepared to deal with hostile incursions into its information systems, and indeed faces a “Digital Pearl Harbor.” Gartzke argues that the Pearl Harbor analogy is indeed an apt one, but not in the ways that its proponents think.

Gartkze’s argument is that cyber incursions are far more likely to cause temporary disruptions than lasting damage. They can surely disrupt a country’s economy or communications, but probably not for very long. This means that they have a military role – but only in combination with other, more conventional forms of attack. He cites the example of Russian attacks on Georgia in their brief war (although his suggestion that these attacks were sponsored by the Russian government is contestable; see the recent article by Ron Deibert et al.) as an example of how this could work. Such attacks could make it easier for a military offensive to succeed, but absent such an offensive they are more likely to provoke than to seriously degrade the military abilities of any adversary. Here, they are indeed like Pearl Harbor, which was less a cunning master plan to destroy a supine America than a desperate throw of the dice by the Japanese, who saw themselves inexorably losing power, and needed to seriously damage the US carrier fleet to have much chance of military success (they failed). Cyberattacks on their own will not have serious military consequences.

Gartzke also argues that it will be extremely difficult for states to use their cyber attack capabilities as a threat to extract concessions from other states. Because cyber attacks rapidly degrade in usefulness (they rely on zero day exploits which can be patched against), and can indeed be countered if they are anticipated, it is hard to make threats that are both (a) credible and (b) not capable of being countered, once the threat is known.

This suggests that cybersecurity incursions are most likely either to accompany traditional attacks (increasing disruption) or to be covert attacks (a la Stuxnet) aimed at disrupting specific and limited systems, without trying to take down an entire economy. If Gartzke is right, much of the hysteria about cybersecurity problems in Washington DC policy debates is utterly misplaced. Cyber security poses some important questions for the US – but not ones that are likely to have grave security consequences.

Hilary Mason, chief scientist at bit.ly, has twoposts on how and why companies like bit.ly should share data with academics. As a beneficiary (together with John and other members of a team of social scientists – we wrote the Arab Spring research that she mentions) of bit.ly’s generosity, I can only applaud. However, there’s one part of her post that deserves some comment. She mentions that bit.ly requires academics who use their data to sign a non-disclosure agreement, but emphasizes how minimal the terms of the NDA are. In particular, under bit.ly’s standard policy:

You may publish whatever you like. Academic freedom FTW.

This is great – but my impression is that bit.ly is unusual in its embrace of academic freedom. From anecdotal evidence, other companies who provide social science academics with access to big data frequently impose much more stringent conditions, aimed, essentially, at ensuring that researchers do nothing that might plausibly be regarded as controversial with their data. Some of this is to the good. Every social scientist has their inner Dr. Marvin Monroe which has to be restrained, forcibly if necessary, when dealing e.g. with personally sensitive data. But some of it is not. It means at the least that it’s going to be very difficult to study e.g. social protest movements with the internal data of international social media companies (if you are a company doing business in a variety of non-democratic regimes, your product’s capacity for stirring up social unrest is unlikely to be a selling point, and hence is something that you will probably discourage researchers from highlighting). This also means that the set of reported findings is going to be a biased sample of the underlying universe of interesting findings that researchers would be reporting if the data were open access (or accessible under minimally restrictive conditions such as bit.ly’s). And in turn, this bias may skew our understanding of the social and political consequences of social media in problematic ways.

Computer scientist Latanya Sweeney turns from her highly influential work on data privacy to investigate patterns in Google AdSense. Specifically, she asks whether the ads that you see when you search for someone by name vary depending on whether you search for a characteristically black or characteristically white name.

First names, previously identified by others as being assigned at birth to more black or white babies, are found predictive of race (88% black, 96% white), and those assigned primarily to black babies, such as DeShawn, Darnell and Jermaine, generated ads suggestive of an arrest in 81 to 86 percent of name searches on one website and 92 to 95 percent on the other, while those assigned at birth primarily to whites, such as Geoffrey, Jill and Emma, generated more neutral copy: the word “arrest” appeared in 23 to 29 percent of name searches on one site and 0 to 60 percent on the other. On the more ad trafficked website, a black-identifying name was 25% more likely to get an ad suggestive of an arrest record. A few names did not follow these patterns: Dustin, a name predominantly given to white babies, generated an ad suggestive of arrest 81 and 100 percent of the time.

It isn’t clear, however, whether this is the result of racially biased expectations on the part of the advertiser, or on the part of people who click on the ads.

Google understands that an advertiser may not know which ad copy will work best, so an advertiser may give multiple templates for the same search string and the “Google algorithm” learns over time which ad text gets the most clicks from viewers of the ad. It does this by assigning weights (or probabilities) based on the click history of each ad copy. At first all possible ad copies are weighted the same, they are all equally likely to produce a click. Over time, as people tend to click one version of ad text over others, the weights change, so the ad text getting the most clicks eventually displays more frequently. … Did Instant Checkmate provide ad templates suggestive of arrest disproportionately to black-identifying names? Or, did Instant Checkmate provide roughly the same templates evenly across racially associated names but society clicked ads suggestive of arrest more often for black identifying names? Google uses cloud-caching strategies to deliver ads quickly, might these strategies bias ad delivery towards ad templates previously loaded in the cloud cache? Is there a combinatorial effect?

Last May, this blog published my essay against building a Death Star. And, not to brag, but at the time I thought we had saved trillions* of lives. With the help of re-posts by Wonkblog, Gizmodo, and legions of social media warriors, the Monkey Cage squelched any thoughts of building a Death Star and saved the lives of countless planets.

Imagine my shock, then, to hear that a petition to the White House had received the 25,000 signatures it needed to force an official response from the White House. I’ve got a bad feeling about this.

ban the development or deployment of a Death Star, or any other moon-sized space station capable of destroying a planet.

Allow me to recapitulate the case against a Death Star:

1) Compared to more discrete alternatives, the Death Star is an inefficient strategy for subduing the population and elites of the galaxy.

2) The money and materials used to build the Death Star would be put to better use upgrading the conventional weapons of the Imperial army.

In the current budgetary environment, the second point is especially important. As we all know, the 2011 debt limit agreement included mandatory reductions in defense spending—the “sequester”—starting in fiscal year 2013. The Department of Defense budget is slated to decrease by $259.4 billion. And yet the advocates for a new Death Star plan to launch it in the midst of this austerity despite its$85.2 quintillion price tag.

Perhaps you are wondering, is an anti-Death Star petition really necessary? Surely the Obama administration will treat the pro-Death Star petition like it’s some sort of joke, even if it means enduring criticism that it is “soft on Alderaan.” Perhaps. But having destroyed the argument for the Death Star once, I was surprised to find that the pro-Death Star forces had moved to in another venue, displacing the local population and threatening the galaxy. I fear they will continue to keep trying until the federal government sets a clear no-Death Star policy.

Via both Cosma Shalizi’s Pinboard feed and an email tip, this map of the geographical origins of racist tweets in the US shows a rather striking pattern.

For a very different representation of geographic data, Mark Newman has some very nice new cartograms of voting in 2012 (Gastner, Shalizi and Newman’s original cartograms of the 2004 election, which received widespread circulation, are still available here ).

This year one of my favorite informal election prediction metrics has been silent: the pizza indicator. In nearly every election year since 2006 either the college Democrats or the college Republicans post signs by the elevators in the Arts and Letters building inviting students to come to a meeting and offering free pizza. The Party offering pizza was the one that won the election in 2006, 2008, 2009 and 2010. (2007 and 2011 were lower turnout state legislative election years with little pizza to be had). This year neither organization is offering pizza, and there has been precious little paper spent even advertising their meetings.

Pizza aside, there are more powerful suggestions that 2012 will be a low turnout election. I focus here on the frequency of Google searches for election-related information. Searches for “vote” should be an indicator of interest in electoral participation. Individuals might search for information on how to vote, or for information on voter registration, and other related information. Therefore, searches for “vote” in Google should provide an indicator of the intensity of citizen interest in voting across states and across elections. More frequent searches for “vote” should predict higher electoral participation.

I tabulated searches for “vote” from September through approximately Election Day in each state for the 2004, 2006, 2008 and 2010 U.S. elections, and compared search volume with state level voter turnout. This comparison is of course only as good as Google’s algorithms that attempt to standardize search volume across time on the same 0 to 100 scale.

The graph below shows the relationship between voter turnout and searches for “vote” in the United States as measured by Google Insights for Search. Overall, the relationship is strong. States in which more people searched for “vote” in a particular election year had higher turnout.

The relationship is also evident after taking account of election year (midterm elections are clustered in the lower left hand portion of the chart). Once election year is taken into account, a shift from 10 to 20 on the search scale is associated with a four percent increase in voter turnout.

If searches for “vote” do predict electoral participation, then 2012 should have lower turnout than 2008 or 2004. The next figure shows nationwide searches for “vote” in 2004, 2008 and (so far) in 2012. (Note that week one is the first week that includes any dates from a given year so week one in 2004 started two days before week one in 2008 and four days earlier than week 1 in 2012, which should bias the 2012 results toward higher numbers as of this writing.)

2012 had lower search frequencies in September at October compared with the last two election years. This implies that if the present trends continue 2012 will also have lower voter turnout.

I also collected the search frequency for “vote” in several swing states (Colorado, Florida, Iowa, Michigan, Nevada, North Carolina, Ohio, Pennsylvania, Virginia, Wisconsin) from September through mid-October. In no instance was the frequency of searches for “vote” higher in 2012 than for previous years. In every case it was substantially lower. Often the search volume was only half of the levels experienced in early election seasons.

Searches for the phrase “register to vote” show the same pattern:

Interest in voter registration peaks in early October, around the time that many states have voter registration deadlines. In 2012 that peak was much lower (58) relative to 2008 (90) and 2004 (100).

The relatively higher internet use among younger voters (and their pronounced tendency to favor Obama) mean that declining search frequency should give particular pause for Democrats. It suggests that interest in this election is lower than in the last two presidential cycles and that turnout will be lower as well. Perhaps some pizza is called for.